%0 Journal Article
%T Design, analysis and presentation of factorial randomised controlled trials
%A Alan A Montgomery
%A Tim J Peters
%A Paul Little
%J BMC Medical Research Methodology
%D 2003
%I BioMed Central
%R 10.1186/1471-2288-3-26
%X Using a 2 กม 2 factorial trial as an example, we present a number of issues that should be considered when planning a factorial trial. The main design issue is that of sample size. Factorial trials are most often powered to detect the main effects of interventions, since adequate power to detect plausible interactions requires greatly increased sample sizes. The main analytical issues relate to the investigation of main effects and the interaction between the interventions in appropriate regression models. Presentation of results should reflect the analytical strategy with an emphasis on the principal research questions. We also give an example of how baseline and follow-up data should be presented. Lastly, we discuss the implications of the design, analytical and presentational issues covered.Difficulties in interpreting the results of factorial trials if an influential interaction is observed is the cost of the potential for efficient, simultaneous consideration of two or more interventions. Factorial trials can in principle be designed to have adequate power to detect realistic interactions, and in any case they are the only design that allows such effects to be investigated.Randomised controlled trials provide the best quality evidence in medical research, [1] but they require a large commitment of time and effort, certainly from the investigators and often from participants. As a result, trials can be expensive. For these reasons, investigators may consider evaluating more than one intervention in the same study. For a controlled trial of two interventions, one could consider a parallel three-arm trial, or even a four-arm trial if two distinct control groups are required. An example is a comparison of mailed guidelines with and without an educational outreach visit from community pharmacists to improve prescribing in general practice.[2] If target differences for both interventions are identical, these would require increases in sample size of 50% and 100% respe
%U http://www.biomedcentral.com/1471-2288/3/26